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https://issues.apache.org/jira/browse/SPARK-32384?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17279293#comment-17279293
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Apache Spark commented on SPARK-32384:
--------------------------------------

User 'zhengruifeng' has created a pull request for this issue:
https://github.com/apache/spark/pull/31480

> repartitionAndSortWithinPartitions avoid shuffle with same partitioner
> ----------------------------------------------------------------------
>
>                 Key: SPARK-32384
>                 URL: https://issues.apache.org/jira/browse/SPARK-32384
>             Project: Spark
>          Issue Type: Improvement
>          Components: Spark Core
>    Affects Versions: 3.1.0
>            Reporter: zhengruifeng
>            Priority: Minor
>
> In {{combineByKeyWithClassTag}}, there is a check so that if the partitioner 
> is the same as the one of the RDD:
> {code:java}
> if (self.partitioner == Some(partitioner)) {
>   self.mapPartitions(iter => {
>     val context = TaskContext.get()
>     new InterruptibleIterator(context, aggregator.combineValuesByKey(iter, 
> context))
>   }, preservesPartitioning = true)
> } else {
>   new ShuffledRDD[K, V, C](self, partitioner)
>     .setSerializer(serializer)
>     .setAggregator(aggregator)
>     .setMapSideCombine(mapSideCombine)
> }
>  {code}
>  
> In {{repartitionAndSortWithinPartitions}}, this shuffle can also be skipped 
> in this case.
>  
>  
>  



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